2015/06/17 by Kamaludin Dingle, Dingle, Kamaludin, Steffen Schaper +3 · 2 citations
Biochemistry, Genetics and Molecular Biology · #Biomolecules (q-bio.BM) #Evolution and Genetic Dynamics #FOS: Biological sciences #Genomics and Phylogenetic Studies #Populations and Evolution (q-bio.PE) #RNA and protein synthesis mechanisms
paper · pdf · doi:10.48550/arxiv.1506.05352
openalex publication_date 2015/06/17 · openalex created_date 2022/10/03 · openalex updated_date 2026/07/28
The prevalence of neutral mutations implies that biological systems typically\nhave many more genotypes than phenotypes. But can the way that genotypes are\ndistributed over phenotypes determine evolutionary outcomes? Answering such\nquestions is difficult because the number of genotypes can be\nhyper-astronomically large. By solving the genotype-phenotype (GP) map for RNA\nsecondary structure for systems up to length L=126 nucleotides (where the set\nof all possible RNA strands would weigh more than the mass of the visible\nuniverse) we show that the GP map strongly constrains the evolution of\nnon-coding RNA (ncRNA). Simple random sampling over genotypes predicts the\ndistribution of properties such as the mutational robustness or the number of\nstems per secondary structure found in naturally occurring ncRNA with\nsurprising accuracy. Since we ignore natural selection, this strikingly close\ncorrespondence with the mapping suggests that structures allowing for\nfunctionality are easily discovered, despite the enormous size of the genetic\nspaces. The mapping is extremely biased: the majority of genotypes map to an\nexponentially small portion of the morphospace of all biophysically possible\nstructures. Such strong constraints provide a non-adaptive explanation for the\nconvergent evolution of structures such as the hammerhead ribozyme. These\nresults presents a particularly clear example of bias in the arrival of\nvariation strongly shaping evolutionary outcomes and may be relevant to Mayr's\ndistinction between proximate and ultimate causes in evolutionary biology.\n